The conventional approaches to oriented texture descriptions are predominantly local or global. We propose a novel translation and rotation invariant generic representation for oriented textures which captures global and local information and this representation can solely be derived from texture intrinsic information. Our approach is demonstrated using texture matching problem in fingerprints domain. The proposed filterbased feature extraction algorithm uses a bank of Gabor filters to extracts both the local and the global details in a fingerprint as a compact 640byte fixed length FingerCode. The fingerprint matching is based on the Euclidean distance between the two corresponding FingerCodes and hence is extremely fast. The results from the experiments are promising and we are able to achieve identification accuracy which is marginally inferior to the best results of minutiaebased algorithms published in the open literature. Our system performs better than a stateoftheart minutiaebased system when the performance requirement of the application system demand low false acceptance rate. Finally, we show that the matching performance can be improved by combining the decisions of the matchers based on complementary fingerprint information.